Usage
linear.hypothesis(model, ...)
lht(...)
linear.hypothesis.lm(model, hypothesis.matrix, rhs=0,
summary.model=summary(model, corr = FALSE),
white.adjust=FALSE, error.SS, error.df, ...)
linear.hypothesis.glm(model, hypothesis.matrix, rhs=0,
summary.model=summary(model, corr = FALSE), ...)
## S3 method for class 'chisq.test':
print(x, ...)
## S3 method for class 'F.test':
print(x, ...)
Arguments
model
model object produced by lm or glm.
hypothesis.matrix
matrix (or vector) giving linear combinations
of coefficients by rows.
rhs
right-hand-side vector for hypothesis, with as many entries as
rows in hypothesis.matrix.
summary.model
a summary object for the model; usually specified
only when linear.hypothesis is called from another function that has
already computed the summary.
white.adjust
if TRUE use heteroscedasticity-corrected covariance matrix.
error.SS
error sum of squares for the hypothesis; if not specified, will be
taken from model.
error.df
error degrees of freedom for the hypothesis; if not specified,
will be taken from model.
x
chisq.test or F.test object.
...
aruments to pass down.